應用存活資料分析
Applied Survival Data Analysis
| 節 | 週二 |
|---|---|
3 10:10–11:00 | 應用存活資料分析 YS221 2 節連堂 |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
能知道存活分析的資料特性,能以適當的方式處理不完備資料, 包括: 1. 存活資料的產生 2. 衡量存活資料的統計方法 3. 無母數分析法、有母數分析法、半參數分析 4. 競爭風險資料分析 Know the characteristics of survival data and be able to analyze the survival data appropriately, including 1. The characteristics of incomplete survival data 2. Measures of survival data 3. Nonparametric models, parametric models and semiparametric models 4. Competing risks data analysis
Lecture notes
HW 50% Final exam 50%
| 週次 | 主題 |
|---|---|
| 第 1 週 | |
| 第 2 週 | |
| 第 3 週 | |
| 第 4 週 | |
| 第 5 週 | |
| 第 6 週 | |
| 第 7 週 | |
| 第 8 週 | |
| 第 9 週 | Introduction 1.Incomplete data property: censoring and truncation2.Typical censoring mechanisms3.Data coding |
| 第 10 週 | Measures for survival data1. Survival rate 2. Survival functions, hazard function and cumulative hazard function |
| 第 11 週 | 1. Nonparametric methods: Kaplan-Meier estimation and real data analysis with R code 2. Nonparametric methods: Log-rank test and real data analysis with R code |
| 第 12 週 | Semiparametric regression models: Cox’s PH model (I) |
| 第 13 週 | Cox’ PH model with stratification. Cox’ PH model with time-varying covariate |
| 第 14 週 | 1. Cox model analysis for the left-truncated and right-censored data 2. logistic-Cox model for the data with a cure fraction. |
| 第 15 週 | Introduction of competing risks data (I), Cause-specific hazard |
| 第 16 週 | Introduction of competing risks data (II), Cumulative incidence function |
| 第 17 週 | Joint modeling for longitudinal and survival data |
| 第 18 週 |
‧ The Statistical Analysis Of Failure Time Data / John D. Kalbfleisch, Ross L. Prentice : c2002 ‧ Statistical Models And Methods For Lifetime Data / Jerald F. Lawless : 2003 (滄海書局) ‧ Survival Analysis: Techniques for Censored and Truncated Data, Statistics for Biology and Health / Klein, John P.; Moeschberger, Melvin L. c1997 ‧ Survival Analysis/ Miller: 1981